Abstract
Cellular heterogeneity is an inherent feature of biological systems, and living single-cell metabolomics (SCM) has emerged as a powerful approach to probe this diversity-a dimension often lost in conventional bulk analyses. Currently, mass spectrometry (MS)-based living SCM techniques are driving a revolution toward higher throughput, sensitivity, and coverage, enabling the identification of rare cell subpopulations and expanding applications across various biological fields. Nevertheless, several bottlenecks remain, including limited metabolome coverage, insufficient throughput, batch effects, instrumental constraints, and challenges in processing large-scale datasets. Future efforts should focus on all stages of SCM, prioritizing the development of microfluidics-integrated living-cell analysis platforms, enhanced ionization sources, in situ chemical derivatizations, AI-powered data processing pipelines, and integrated multi-omics analyses at the single-cell level. Despite existing hurdles, continuous progress in technology, data science, and interdisciplinary collaboration is expected to bring transformative breakthroughs in MS-based living SCM, ultimately advancing our understanding of dynamic biological processes and accelerating biomedical discovery.